Implementation of Deep Deterministic Policy Gradients for Controlling Dynamic Bipedal Walking

A control system for bipedal walking in the sagittal plane was developed in simulation. The biped model was built based on anthropometric data for a 1.8 m tall male of average build. At the core of the controller is a deep deterministic policy gradient (DDPG) neural network that was trained in GAZEB...

Descripción completa

Detalles Bibliográficos
Autores principales: Liu, Chujun, Lonsberry, Andrew G., Nandor, Mark J., Audu, Musa L., Lonsberry, Alexander J., Quinn, Roger D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6477666/
https://www.ncbi.nlm.nih.gov/pubmed/31105213
http://dx.doi.org/10.3390/biomimetics4010028

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6477666/
https://www.ncbi.nlm.nih.gov/pubmed/31105213
http://dx.doi.org/10.3390/biomimetics4010028

Ejemplares similares